Video surveillance systems are commonly used to monitor indoor and outdoor areas using video cameras positioned at various locations within the area to be monitored. Video surveillance systems are commonly implemented via networks of multiple surveillance cameras to facilitate monitoring of large areas. In order for a surveillance system including multiple cameras to operate intelligently, the cameras are calibrated so that they are aware of their location and the location of other cameras nearby. This calibration enables cameras within the system to cooperate in an intelligent manner, which in turn enables inter-camera analytics to be employed within a surveillance system and opens up possibilities for more intelligent video and audio analytics within the system.
In existing surveillance systems, the location of each camera in the system is manually provided, e.g., as user input. However, manual entry of camera locations is tedious and prone to errors and inaccuracies. As the number of cameras in the surveillance system increases, the probability that one or more cameras in the system are associated with incorrect and/or inaccurate position information similarly increases. These location errors can, in turn, reduce the ability of the cameras to operate together in an effective manner.